Fix incompatibility with latest pandas/scipy

.gitignore

@@ -34,3 +34,6 @@ infercnv_env/
 
 # Node.js
 node_modules/
+
+# uv
+uv.lock

pyproject.toml

@@ -24,7 +24,7 @@ urls.Source = "https://github.com/icbi-lab/infercnvpy"
 urls.Home-page = "https://github.com/icbi-lab/infercnvpy"
 dependencies = [
     'anndata>=0.7.3',
-    'scanpy>=1.6.0',
+    "scanpy>=1.9",
     'pandas>=1',
     'numpy>=1.20', # includes type annotations
     'tqdm>=4.63.0', # fixes tqdm.auto
@@ -36,7 +36,6 @@ dependencies = [
     'pytest-benchmark',
     # for debug logging (referenced from the issue template)
     "session-info",
-    "ipython"
 ]
 
 [project.optional-dependencies]

src/infercnvpy/pl/_chromosome_heatmap.py

@@ -147,7 +147,7 @@ def chromosome_heatmap_summary(
     tmp_obs.index = tmp_obs.index.astype(str)
 
     def _get_group_mean(group):
-        group_mean = np.mean(adata.obsm[f"X_{use_rep}"][adata.obs[groupby] == group, :], axis=0)
+        group_mean = np.mean(adata.obsm[f"X_{use_rep}"][adata.obs[groupby].values == group, :], axis=0)
         if len(group_mean.shape) == 1:
             # derived from an array instead of sparse matrix -> 1 dim instead of 2
             group_mean = group_mean[np.newaxis, :]

src/infercnvpy/tl/_infercnv.py

@@ -98,7 +98,7 @@ def infercnv(
         raise ValueError("Ensure your var_names are unique!")
     if {"chromosome", "start", "end"} - set(adata.var.columns) != set():
         raise ValueError(
-            "Genomic positions not found. There need to be `chromosome`, `start`, and " "`end` columns in `adata.var`. "
+            "Genomic positions not found. There need to be `chromosome`, `start`, and `end` columns in `adata.var`. "
         )
 
     var_mask = adata.var["chromosome"].isnull()
@@ -388,7 +388,7 @@ def _get_reference(
                     f"{reference_cat[~reference_cat_in_obs]}"
                 )
 
-            reference = np.vstack([np.mean(adata.X[obs_col == cat, :], axis=0) for cat in reference_cat])
+            reference = np.vstack([np.mean(adata.X[obs_col.values == cat, :], axis=0) for cat in reference_cat])
 
     if reference.ndim == 1:
         reference = reference[np.newaxis, :]

src/infercnvpy/tl/_scores.py

@@ -63,7 +63,7 @@ def cnv_score(
     if groupby not in adata.obs.columns and groupby == "cnv_leiden":
         raise ValueError("`cnv_leiden` not found in `adata.obs`. Did you run `tl.leiden`?")
     cluster_score = {
-        cluster: np.mean(np.abs(adata.obsm[f"X_{use_rep}"][adata.obs[groupby] == cluster, :]))
+        cluster: np.mean(np.abs(adata.obsm[f"X_{use_rep}"][adata.obs[groupby].values == cluster, :]))
         for cluster in adata.obs[groupby].unique()
     }